# NumpyGCN

**Repository Path**: ShawLen/numpy-gcn

## Basic Information

- **Project Name**: NumpyGCN
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-06-08
- **Last Updated**: 2021-06-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# CS 6787 Final Project: Graph Convolutional Network Analysis

In this repository we implement a Graph Convolutional Network using exclusively python primitives and compare its performance with Thomas N. Kipf, Max Welling, [Semi-Supervised Classification with Graph Convolutional Networks](http://arxiv.org/abs/1609.02907) (ICLR 2017)'s TensorFlow and Pytorch implementation. 

For more information on Graph Convolutional networks see [GCN](http://tkipf.github.io/graph-convolutional-networks/)

## Numpy Implementation

```bash
python numpyGCN/train.py
```

## TensorFlow Implementation

First run...
```bash
python tfGCN/setup.py install
```

and then 
```bash
python tfGCN/train.py
```

## PyTorch Implementation

```bash
python torchGCN/train.py
```